Issue |
Aquat. Living Resour.
Volume 37, 2024
|
|
---|---|---|
Article Number | 13 | |
Number of page(s) | 9 | |
DOI | https://doi.org/10.1051/alr/2024011 | |
Published online | 23 September 2024 |
Research Article
Assessing stock of reef octopus Octopus cyanea in southwest Madagascar using age-based population modelling
1
Institut d’Enseignement Supérieur d’Anôsy, Université de Toliara, Fort-Dauphin BP 131, 614, Madagascar
2
Aix-Marseille Université, CNRS, IRD, INRAE, CEREGE, 13545 Aix-en-Provence, France
* Corresponding author: andrisoa@cerege.fr
Received:
20
October
2023
Accepted:
21
August
2024
The reef octopus Octopus cyanea fishery is the most economically important fishery in southwest Madagascar. The substantial increase of octopus exploitation in the region has raised concerns over the sustainability of this fishery. While a growing number of measures have been implemented to sustainably manage the octopus stock, there is a lack of information on the status of this octopus stock. In this study, we analyse the status of octopus stock in southwest Madagascar by investigating the interannual and seasonal variability in recruitment and fishing mortality using virtual population analysis (VPA) performed on monthly basis from 2020 to 2022. Yield per recruit is also predicted using a Thomson and Bell model. Our results indicate that octopus fishery national closures (December 15 to January 31 each year) result overall in increase of catches and stock biomass, evidencing the positive impacts of the implemented fisheries regulations in the region. Recruitment exhibits high interannual and seasonal variability with a peak observed between October and December. The simulation model suggests that yield per recruit remains almost unchanged from one year to the next and not exceeding the maximum yield per recruit. Overall, this study shows the importance of understanding the status of octopus stock for sustainable octopus fisheries in southwest Madagascar.
Key words: Fishery / Octopus cyanea / Madagascar / stock assessment / virtual population analysis / recruitment
Handling Editor: François Le Loc'h
© D. Raberinary and A. Andrisoa, Published by EDP Sciences 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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